Topics for Test 2.  
(release date Monday 11/16/20)


From Chapter 6: Dimensionality Reduction
        6.3: Principal Component Analysis
        6.6: Singular Value Decomposition and Matrix Factorization

From Chapter 7: Clustering
        7.3: k-Means Clustering
        7.4: Expectation-Maximization Algorithm
	Class Notes

From Chapter 8: Nonparametric Methods
 	8.2.3 k-Nearest Neighbor

From Chapter 13: Kernel Machines
        13.1: Introduction
        13.2: Optimal Separating Hyperplane
        13.3: The Nonseparable Case: Soft Margin Hyperplane
        13.5: Kernel Trick
	Bennett & Campbell paper